Presentation is about genetic algorithms. Also it includes introduction to soft computing and hard computing. Hope it serves the purpose and be useful for reference.

1. Genetic Algorithm Made By -Garima Singhal

7. Difference between Soft computing And Conventional Computing Hard Computing(Conventional) Soft Computing Requires precisely stated analytical model and a lot of computation time. Tolerant of imprecision, uncertainty and approximation. Based on binary logic, numerical analysis and crisp software. Based on fuzzy logic, neural networks and probabilistic reasoning. Requires programs to be written. Can evolve its own programs. Deterministic. Incorporates stochasticity. Strictly sequential. Allows parallel computations.

19. Working Principle of Genetic Algorithm

22. The fitness function and chromosome locations

34. The GA Cycle of Reproduction Population Fitness Evaluation Genetic Operators Selection(Mating Pool) Parents Offspring New Generation Manipulation Reproduction Decoded Strings

37. Genetic Algorithm Applications Domains Application Types Control Gas pipeline, pole balancing, missile evasion, pursuit Robotics Trajectory planning Signal Processing Filter design Game Playing Poker, checker, prisoner’s dilemma Scheduling Manufacturing facility, scheduling, resource allocation Design Semiconductor layout, aircraft design, keyboard configuration, communication networks Combinatorial Optimisation Set covering, travelling salesmen, routing, bin packing, graph coloring and partitioning

38. Any Questions